Marco Trincavelli and Amy Loutfi
Feature Selection for Gas Identification with a Mobile Robot
Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), May 3-8, 2010, Anchorage, Alaska.
Abstract: In this paper we analyze the problem of discrimination of gases with mobile robots. Previously, it has been shown that the conditions in which data is collected heavily influence the characteristics of the signal to be identified. As a result, the already difficult task of selecting features which characterize a gas is made more challenging by the absence of a steady state response. This is often due to the movement of the robot, and/or the physical properties of the environment, e.g., turbulent airflow creating patches and eddies in the plume. In this work we compare two approaches for feature selection which are able to consider explicitly the information on the experimental setup and optimize the subset of features used in the recognition process. The approaches are tested on a large data set collected with a mobile robot moving in different environments (outdoors and indoors). The results show that the classification performance is improved resulting in a higher average accuracy and lower variance in the accuracy across the different experimental setups.
Keywords: Mobile Robotics Olfaction, Gas Discrimination, Feature Selection.
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@INPROCEEDINGS{Trincavelli_Loutfi:ICRA:2010,
  AUTHOR = {Trincavelli, Marco and Loutfi, Amy},
  TITLE = {Feature Selection for Gas Identification with a Mobile Robot},
  BOOKTITLE = {Proceedings of the IEEE International Conference on Robotics and Automation (ICRA)},
  YEAR = {2010},
  DATE = {May 3--8},
  ADRESS = {Anchorage, Alaska, USA},
  PAGES = {2852 - 2857}
  DOI = {10.1109/ROBOT.2010.5509617}
}